Sarah has always had some pretty interesting takes, excited to hear more from her regularly. Also the production value is great!!
“Do you think that getting married young has made you less ambitious?”
Welcome to the first episode of SOTA Wives with Sarah Chieng (Head of DevX at Cerebras, @MilksandMatcha) x Vivian Midha Shen (General Partner at Y Combinator, @vivianmshen).
In episode 1: finding your person before getting rich, turning down startup funding to finish MIT, what a YC partner sees in founders, and how a birthday post became “psychological violence.”
4:08 Finding your husband before the exit
8:48 Did we marry away our ambition?
18:04 The internet called Sarah's birthday “psychological violence”
20:47 Does your YC partner secretly think you’re doomed?
23:47 Building a startup with your ex-boyfriend
28:54 SF cat parties
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Can't wait for this era of babysitting to be over honestly
I’ve seen this firsthand:
Vibe coding fails when you can’t tell the difference between a "best practice" on paper and real-world experience. Real experience means factoring in all the trade-offs, from speed and cost to safety, and making the pragmatic choice, which even the best models can’t do. Here are some examples:
1. Data migrations. The model proposed a fleet of parallel cloud functions and new insert endpoints, adding endpoint, invocation, logging, and telemetry costs.
The database was the bottleneck anyway, so a single remote server would have been enough. An agent could run the migration script there, detect unexpected data formats, update the script, and continue migrating as it encountered edge cases. It would have shipped and run twice as fast at half the cost.
2. Database constraints. Models love putting every business rule and enum constraint in the database.
That sounds robust, but it can make shipping painfully slow. Every new enum value or business rule change becomes another database migration. Application-level validation is usually enough. Otherwise, monitor for inconsistencies and alert.
3. Missing variables. Models often add fallback values when an environment variable is missing.
It keeps the app running, which feels convenient, especially during local development. But if infrastructure forgets to set a required variable or uses the wrong name, the app can silently run in development mode. The safer behavior is to fail loudly at startup so the deployment will halt.
Knowing how to code matters because you need to recognize when the model’s "best practice" is wrong and override it.
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The future is heading here: agents configuring agents. Expertise, even of this meta kind, is becoming accessible through AI.
Giga Browser Agent
We work on some of the largest enterprise AI deployments in the world and learned automation outcomes are more often first blocked by API access than they are blocked on model capabilities...
Introducing Giga's browser agent.
Giga can now log in and completes tasks end-to-end, just like your human agents.
It used to take months to get support APIs deployed for AI agents in the enterprise. Now these integrations can be built instantly.
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Huge feature for @GigaAI — Nasdaq tower ✅
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🧵 Understanding this concept deeply is fundamental to what makes @GigaAI so special. It's one of the biggest reasons I joined (beyond getting the chance to work with @eshamanideep and @varunvummadi).
The “forward deployed” concept will cause harm to many startups that go down this path. When you are building the product, park yourself at customers’ office. But, the goal should be to build a great product that does not require you to forward deploy a person for the customer to be successful. If you solve problems with people, you will default to throwing bodies at problems and will build an inferior product. Your goal should be the opposite.
Come see @eshamanideep (our CTO) talk about @GigaAI at @ycombinator HQ on December 10th! I'll be there as well.
We're hiring the most ambitious engineers across the stack to build the future of AI support agents for the largest B2C companies in the world.
Link below
Couldn't have said it myself. @gigaai has the best product hands down. That's why we are already winning with the best companies on the most complicated use cases.
So many markets look like crowded spaces until you actually take a closer look at who is actually competing. This is a vast ocean and Giga is here to win the whole thing.
"Don't build anything custom for the customer. Everything has to be a core part of the product."
This is an enormous part of why @gigaai is different.
Thanks @harjtaggar for helping us tell this part of our story.
Something that stunned me about @gigaai is they've moved away from the FDE playbook that's become the default for fast growing AI startups. Instead they've built AI to covert plain English from the customer into Python code to make the product work for their use cases i.e. an AI FDE. It's a huge technical feat and is how they can onboard enterprises in weeks vs months.
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Giga $61M Series A
I met @eshamanideep and @varunvummadi in Jan 2024 at a @ycombinator event. @harjtaggar introduced them — he had noted they were wicked smart and gritty.
An incredible milestone by the @gigaai team.
It's been breathtaking working alongside everyone who made this happen. Each person on the team has an unparalleled sense of urgency and purpose.
We're here to build a generational startup that conquers the most challenging operational problems for the world's largest B2C companies.
If you're interested, I'm helping @eshamanideep and @varunvummadi scale the engineering team ASAP – check out our careers page below
Excited to share our partnership with DoorDash.
Together we went from kickoff to real impact — in weeks, not quarters.
Highlights:
- Time to value: weeks, not quarters
- Quality at scale: 90%+ DWR in production
- Built for scale: 10B+ lifetime orders, 500K+ merchants, 8M+ Dashers, and hundreds of thousands of daily assistance requests
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I’ve joined @gigaai as Head of Product.
I met @varunvummadi & @eshamanideep at @ycombinator when it was their first time in America. They’ve since scaled their voice AI platform to handle millions of calls for companies like DoorDash 🚗
I’m helping Giga build what comes next. If you’re an engineer, designer, or operator who’s obsessed with scale, autonomy, and impact, I’d love to talk.
Let’s move the world towards perfect execution with AI.
High interest rates are good actually, expands access to credit.
If lenders can’t profitably lend to demographics that are likely to default, they won’t lend.
I look forward to working with the Trump Administration on fulfilling his promise to cap credit card interest rates at 10%.
We cannot continue to allow big banks to make record profits by ripping off Americans by charging them 25 to 30% interest rates.
That is usury.
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Nice writeup. I’ve noticed low-code-no-code occupies the “else” statement space well — a higher-ordered 911 for when off the shelf point solutions and platforms fail, traditionally occupied by internal tools and consulting
Kevin Kwok wrote of the concept kwokchain.com/2019/08/16/the…
I wrote a long essay on why most of the low-code-no-code tool builders haven't made it out of the teenage slumps -- Airtable & Retool are big ones that come to mind. Warning: it's LONG. docs.google.com/document/d/1…
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